Audit and consolidate a fact that's scattered across places into one canonical source, after approval, and replace the rest with references. Use when asked to find duplication, check consistency, locate the source of truth, deduplicate, consolidate, unify, or establish SSOT across artifacts or platforms. Starts read-only, reports the map and plan, then mutates only after explicit approval.

Hybrid fingerprint + LLM pipeline for bug classification, deduplication, and ticket generation. Normalizes CI logs, creates stable fingerprints, clusters near-duplicates, then uses LLM for severity classification and ticket writing. Includes bug reporting templates and severity/priority matrix. Use when: "bug triage," "classify bugs," "failure analysis," "auto-classify," "CI failures," "bug report," "defect template." Not for: runtime self-healing of one flaky locator — use test-reliability. Not

Consolidates raw security findings to eliminate redundant reports. Use when raw findings have been generated by the researcher and need consolidation before review. Don't use for initial code auditing or patch generation.

Use when working with n8n's built-in Data Tables, designing schemas, inserting/updating/upserting rows, deduping, or querying. Triggers on "Data Table", "data table", `n8n-nodes-base.dataTable`, "dedup", "idempotency", "lookup", "persistent state", "store across executions", or any schema design discussion inside n8n.

Find incomplete records, normalize field values in bulk, dedupe with `hubspot objects merge`, and audit custom properties. Builds on `bulk-operations` for JSONL piping and dry-run/digest/confirm.

Scan the Obsidian wiki for page-level identity collisions — different pages covering the same concept under different names (e.g. "RSC" vs "React Server Components") — and merge them. Use this skill when the user says "dedup my wiki", "find duplicate pages", "merge duplicates", "identity resolution", "consolidate my wiki", "I have duplicate pages", or "my wiki has two pages for the same thing". Distinct from wiki-lint (which checks structure) and cross-linker (which adds links) — this skill make

Combines search results from multiple sources into coherent, deduplicated answers with source attribution. Handles confidence scoring based on freshness and authority, and summarizes large result sets effectively.

Maintains memory cleanliness with deduplication, validation, and expiration